Data compression is a useful tool for storing and transmitting large amounts of data. For example, the time required to transmit an image, such as a facsimile transmission of a document, is reduced when compression is used to decrease the number of bits required to recreate the image.
Many different data compression techniques exist in the prior art. Compression techniques can be divided into two broad categories, lossy coding and lossless coding. Lossy coding involves coding that results in the loss of information, such that there is no guarantee of perfect reconstruction of the original data. The goal of lossy compression is that changes to the original data are done in such a way that they are not objectionable or detectable. In lossless compression, all the information is retained and the data is compressed in a manner which allows for perfect reconstruction.
In lossy compression, numeric data such as signal or intensity data, or a transformed form thereof, are quantized prior to conversion to output codewords. Quantization is intended to preserve relevant characteristics of the data while eliminating unimportant characteristics. Prior to quantization, lossy compression system often use a transform to provide energy compaction. JPEG is an example of a lossy coding method for image data.
Data in a transform-coded compressed set of data, such as a compressed image file, are transform coefficients. The compressed data represent integer values to which these coefficients have been rounded. Most of the rounded coefficients are zero. However, due to statistical coding, most of the bits in the compressed file are spent on detailing the non-zero coefficients.
The least significant bits of the coefficient, or other codeword, are relevant only when the SNR of the compression device is 6.02 decibels above the relevance level of the bits next in significance to the least significant bits. Many times, the least significant bit has very little effect whatsoever on decompressed signal quality. It would be desirable to eliminate the least significant bit when it does not provide any added value in the compressed set of data. But in JPEG and many similar methods such bits serve as place holders in the compressed file.
Another approach to recover some of the space that is essentially wasted in the compressed file due to inclusion of least significant bits is set forth in Silverstein and Klein, "Restoration of Compressed Image," Proceedings of SPIE on Image and Video Compression, pp. 56-64, vol. 2186, February 1994, San Jose, Calif. In Silverstein and Klein, coefficients near a threshold are handled specially to provide a separate lossless channel embedded with the ordinary bits of the least significant bit channel.
The present invention provides a technique for reducing the number of least significant bits in a set of compressed data (e.g., compressed files), while enhancing rate-distortion performance.